Genetic aberrations that cause a gain or loss of chromosomal material are associated with mental retardation and congenital malformations and linked to development of cancer. Comparative genomic hybridization (CGH) is making strides as a powerful tool for analyzing such DNA copy-number alterations. This emerging technology is poised to reap big rewards in the burgeoning molecular diagnostics market. Further, as CGH’s precision and reliability continue to grow, important uses in the clinic and for personalized medicine will advance.
How does it work? Typically, genomic DNA from test and reference are isolated, differentially labeled, and then hybridized with DNA microarrays. The relative amount of hybridization signal is proportional to the copy number of the sequences tested. So-called CNPs (copy-number polymorphisms) are areas in the genome with altered DNA copy numbers. Identifying regions of genomic gains or losses can reveal chromosomal aberrations and define relative phenotypes within the population. Detecting and interpreting such aberrations can identify genes and pathways involved in pathological states.
Although microarrays for gene expression have been available for several years, arrays for CGH are fairly new, with usage growing at a tremendous pace, according to Condie E. Carmack, Ph.D., program manager, microarrays, diagnostics, Agilent Technologies (www.agilent.com).
“Array CGH (aCGH) provides an efficient means to determine changes in genomic copy number as well as transition points,” notes Dr. Carmack. “In a recent study, we applied high-resolution microarray-based aCGH analysis to FFPE breast cancer samples.” Dr. Carmack’s team used the company’s 244K CGH array, which consists of 244,000 in situ synthesized 60-mer oligonucleotide probes on a single 1x3 inch slide. The long probes are designed to offer high sensitivity and selectivity to improve the results of aCGH experiments, explains Dr. Carmack.
“It’s important to accurately determine copy number transitions and boundaries to define the genes that lie within aberrations. CGH provides this information, but working with FFPE samples can be challenging. This type of sample is often difficult to work with, because the fixatives interfere with the enzymes used to label DNA. But, we do not use enzymes, we use a universal labeling system from Kreatech (www.kreatech.com).”
There are an estimated 400 million FFPE-preserved samples in tissue banks worldwide, underscoring the value of their use for analyzing DNA and genetic associations related to diseases such as cancer and autism.
Dr. Carmack’s studies identified three different classes of samples based on their CGH profile, two of which indicated a poor prognosis/survival outcome class and one that correlated with a good prognosis/survival outcome class.
“Overall, our studies help identify hot spots in the genome. In fact, we are seeing that the genome is much more dynamic than previously realized. Genes frequently amplify, replicate, and delete. Cancers can use these hot spots to gain growth advantages over normal cells. Identifying these areas associated with abnormal growth can lead to a targeted therapy, like in the case of Herceptin.”
Dr. Carmack expects that Agilent’s array will increase to a million features within a few months, offering even more information with no decrease in signal quality. The greater density is designed to drive resolution up while driving costs down, according to Dr. Carmack. “It is similar to increasing the pixel resolution on your digital camera.”
Some of the applications for aCGH technology are genotyping and medicinal genetics, reports Dr. Carmack. “All individuals have their own unique profile that shows familial, racial, and idiotypic differences, and these can be identified by genotyping. Secondly, we expect to see CGH used increasingly for personalized medicine.
For example, a drug might be dosed depending on how many copies a patient has of a particular gene impacted by the drug. If the gene is deleted, the patient might be too sensitive, while if they have 10 copies, they may need 10 times the dose. We know that people react differently to different drugs, and CGH will help the medical community get a much better handle on dosing.”
Making Sense of Massive Data Sets
Array CGH is an efficient approach for scanning entire genomes to seek variations in DNA copy number. “The technique of array CGH is changing from being only a research tool to being a tool for clinical diagnostics,” explains Anton Petrov, Ph.D., scientific director at infoQuant (www.infoquant.com). “But this requires a new generation of analytical solutions that can reliably and automatically report copy-number changes.”
InfoQuant offers two software products to assist with this analysis. “Our CGH Fusion™ analyzes CGH data across multiple samples,” says Dr. Petrov. “Ultimately, researchers want to be able to access information about the comparative frequency of appearance of each region of chromosomal aberration in patients with similar disorders and then compare that to healthy patients. CGH Fusion can find areas of common copy-number changes within the same biological condition. It is also scalable and user-friendly.”
The second product, oneClickCGH™, facilitates automated analysis of array CGH data on a per-patient basis. “This package allows a diagnostician to analyze low- and high-resolution data from various array CGH platforms. Discovered chromosomal regions are compared to various publicly available databases such as Entrez, Database of Genomic Variants (DVV), or the UCSC Genome Browser. This type of application is helpful for diagnosticians since they can use it to discover regions of a chromosome where if the copy number is changed, there is an increased risk of a disorder.”
More than 178,000 U.S. women are diagnosed with invasive breast cancer each year, with approximately 41,000 fatalities. CGH is being utilized along with other technologies to identify ethnic-specific differences. “These differences are increasingly evident in both stage at presentation as well as survival rates,” according to Lisa Baumbach-Reardon, Ph.D., associate research professor and director of molecular genetics for the Miami GeneCure Diagnostic Laboratory at the Dr. John T. MacDonald Foundation Center for Medical Genetics, University of Miami.
“We are investigating the genetic basis for these differences,” reports Dr. Baumbach-Reardon. “We initially studied African-American women and now are pursuing a multiethnic cohort consisting of 20 patients who are matched for age of diagnosis, cancer stage, and hormone-receptor status.”
To perform these studies, Dr. Baumbach-Reardon’s team characterizes DNA copy number and chromosome alterations by CGH arrays and also examines RNA expression differences in microarrays. “These technologies when applied together are even more powerful than if done alone because they help identify the multiple mechanisms involved. We are asking questions at the whole-genome level and are finding some interesting data. There are inherent variations in ethnicity and sorting out normal variations from pathological ones is the challenge.”